Estrogen receptor (ER) is the most important prognostic marker recognized in breast cancer. The presence of ER indicates a good prognosis and the tumors likely to respond to anti-estrogen therapies. Recent studies have shown that some tumor cells express ERbeta and several spliced variants in addition to classical ERalpha and their presence correlate with prognosis and response/resistance to anti-estrogen therapies. In vitro studies have demonstrated that alpha, beta and the splice variants have distinct ligand binding and transcriptional properties. It strongly follows that the relative proportion of various ERs will result in different ligand- and DNA binding properties and the response to a particular anti-estrogen therapy depends on relative amounts of all Isoforms. Our long range goal is to improve patient survival by understanding how the expression profiles of various ERs in tumors can be applied for prognostic and therapeutic decisions. The objective of this application is develop a clinically applicable assay that can precisely quantify all ER isoforms from a small amount of tumor tissue and establish a correlation between ER profiles and disease outcomes. The rationale for the proposed research is that, once the composition(s) of ERs which correlates with disease outcomes are understood, they can be applied to select treatment options. Currently, the prognostic predictions and therapeutic decisions are made based on the presence of only ERalpha as detected by immunohistochemistry. The problem is that this method 1) cannot effectively distinguish all the known ER forms, 2) is not highly sensitive, and 3) requires a large amount of tumor tissue to quantify all ER forms. We propose to develop a Real-Time quantitative PCR assay that can accurately define the proportion of the total represented by each of the ER forms. To accomplish the objective of this application, we will pursue two specific alms: 1) Establish a correlation between the mRNA profiles of various ERs and ligand binding and response and 2) Identify the ER mRNA profiles by Real-time PCR that correlate with tumor stage, nodal status, histological type, prognosis and response/resistance to anti-estrogen therapies. We are poised to develop the above assay, because it capitalizes on the novel approaches for 1) quantifying various forms of ERs 2) specific methods to amplify spliced ERs which were developed by our group and 3) the availability of tumor tissues, in addition to successful completion of "Evaluation Phase of the assay development". It is our expectation that the resultant clinically applicable assay will permit us and others to generate data that allow definitive correlation between the status of various forms of ER with: 1) prognosis and 2) response to anti- estrogen as well as other therapies. Such outcomes will be significant for the breast cancer patients who are resistant or acquire resistance to anti-estrogen therapies.